Machine-learning method for conditioning individual or shared areas

ABSTRACT

A method and system for conditioning an interior area is disclosed. A method includes retrieving environmental conditions regarding the interior area, wherein the environmental conditions include temperature, humidity, and air speed; retrieving outdoor environmental conditions; generating a field of environmental conditions at a plurality of points within the interior area; estimating clothing insulation of a user based on the outdoor environmental conditions; calculating a thermal comfort of the user to determine a predicted mean vote; and operating a heating, ventilation, and air conditioning system based on the calculated thermal comfort.

BACKGROUND

Exemplary embodiments pertain to the art of electronics. In particular, the present disclosure relates to a method and system for integrating machine-learning capabilities with conditioning whether they are occupied by an individual or groups.

Thermal comfort in an indoor location is achieved through the use of heating, ventilation, and air conditioning (HVAC) units placed throughout the indoor location. HVAC can be very expensive, representing up to 65 percent of energy consumption of a building.

In the past, there have been many different ways of controlling the thermal comfort and thus the energy consumption. A very approximate way of doing so is to manually control air conditioning and heating units—turning them on and off as needed, depending on if a building's occupants are comfortable. Later, thermometers were added—if too high temperature was sensed, an air conditioning system could be switched on and if too low a temperature was sensed, a heating system could be switched on. It would be desirable to have a more efficient and accurate method of setting a thermal comfort level of an indoor area.

BRIEF DESCRIPTION

According to one embodiment, a method and system for conditioning an interior area is disclosed. A method includes retrieving environmental conditions regarding the interior area, wherein the environmental conditions include temperature, humidity, and air speed; retrieving outdoor environmental conditions; generating a field of environmental conditions at a plurality of points within the interior area; calculating a thermal comfort of the user to determine a predicted mean vote; and operating a heating, ventilation, and air conditioning system based on the calculated thermal comfort.

In addition to one or more features described above, or as an alternative, further embodiments may include retrieving usage information regarding the interior area.

In addition to features described above, or as an alternative, further embodiments may include estimating clothing insulation of a user based on the outdoor environmental conditions and the usage information.

In addition to features described above, or as an alternative, further embodiments may include receiving feedback from the user regarding the user's comfort level; and operating the heating, ventilation, and air conditioning system based on the feedback.

In addition to features described above, or as an alternative, further embodiments may include storing the feedback in a thermal profile associated with the user.

In addition to features described above, or as an alternative, further embodiments may include wherein calculating the thermal comfort of the user comprises using the thermal profile to calculate the thermal comfort.

In addition to features described above, or as an alternative, further embodiments may include wherein calculating the thermal comfort of the user comprises using a Fanger equation to calculate the predicted mean vote.

In addition to features described above, or as an alternative, further embodiments may include wherein the predicted mean vote is on a continuous scale ranging from −3 to 3, wherein a value of −3 indicates a cold thermal condition and a value of 3 indicates a warm thermal condition.

In addition to features described above, or as an alternative, further embodiments may include calculating the thermal comfort for each user of a plurality of users in the interior area; and calculating an average thermal comfort for the plurality of users; wherein operating a heating, ventilation, and air conditioning system is based on the average thermal comfort of the plurality of users.

In addition to features described above, or as an alternative, further embodiments may include calculating a predicted percentage of dissatisfied users based on the thermal comfort of each of the plurality of users; wherein: operating a heating, ventilation, and air conditioning system further comprises ensuring that the predicted percentage of dissatisfied users is below a predetermined threshold.

BRIEF DESCRIPTION OF THE DRAWINGS

The following descriptions should not be considered limiting in any way. With reference to the accompanying drawings, like elements are numbered alike:

FIG. 1 is a flowchart illustrating the operation of one or more embodiments;

FIG. 2 illustrates various equations used in one or more embodiments;

FIG. 3 is a block diagram of a computer system capable of performing one or more embodiments; and

FIG. 4 is a block diagram of an exemplary computer program product.

DETAILED DESCRIPTION

A detailed description of one or more embodiments of the disclosed apparatus and method are presented herein by way of exemplification and not limitation with reference to the Figures.

The term “about” is intended to include the degree of error associated with measurement of the particular quantity based upon the equipment available at the time of filing the application.

The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the present disclosure. As used herein, the singular forms “a”, “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises” and/or “comprising,” when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, element components, and/or groups thereof.

As described above, indoor locations, such as office buildings, warehouses, homes, apartments, classroom buildings, retail locations, and the like, often have heating, ventilation, and air conditioning (HVAC) systems to help maintain the indoor location at a desired temperature. While there are manual controls to turn HVAC systems on and off, most modern HVAC systems are controlled by a thermostat. A thermostat has a temperature sensor at one or more locations. Based on the temperature sensed at that location, the thermostat can turn portions of an HVAC system on and off.

In one or more embodiments, machine-learning methods and systems can be used to monitor and learn thermal comfort levels of occupants. Using voting techniques, one or more embodiments can determine a comfort level of each occupant of a group of occupants. Thereafter, a thermal profile can be updated based on the received feedback.

A thermal profile is used to determine if a user would be comfortable at a range of interior climate conditions. In some embodiments, this can be measured using a Thermal Comfort algorithm. The thermal profile includes temperature of the room. In some embodiments, a thermal profile also can include aspects of the room, such as relative humidity, air velocity, and radiation (mean radiant temperature), as well as characteristics of the user, such as metabolic rate of the user, and the clothing worn by the user. While the aspects about the room can be measured using one or more of a variety of different sensors, the characteristics of the user can be estimated.

Estimating the characteristics of the user can utilize a variety of information known about the user, the time of day, and potential tasks of the user. Metabolic rates have been estimated for a wide variety of different tasks. For example, the National Institute of Health has published tables that provide a variety of Metabolic Equivalent values for a variety of activities, where 1 Met is equal to 58.15 watts per square meter of body surface. Because the average adult has 1.7 square meters of surface area, 1 Met is equivalent to a heat loss of approximately 100 watts. To provide examples, sleeping generates 0.92 Met, preparing food generates 2.16 Met, playing basketball generates 8.00 Met, and doing homework generates 1.66 Met.

Based on the building layout, an estimated MET value for a user can be estimated based on the activities predicted to be taking place in a room in which the user is located. A conference room would have a lower MET value than a basketball gym, but would have a higher MET value than a bedroom.

Clothing worn can be estimated based on the season, the time of day, outdoor weather conditions, as well as the intended use of the interior space. For example, people wearing business attire have a different amount of clothing insulation than people in a workout facility. During cold weather, people near the entrance of a hotel are wearing additional layers clothing they were wearing outside, but people in hotel rooms often take off their coats. Clothing can be classified by its insulation value. Insulation value may be measured in Clo, where 1 Clo is equal to 0.155 m²° C./W. There are readily available Clo values for typical pieces of clothing. The Clo value for a person would then be the Clo value for each piece of clothing they are wearing. A person wearing shorts, a shirt, socks, and shoes, may have a Clo value of 0.38, while a person wearing casual work clothes may have a Clo value of 0.91.

As stated above, the remaining data points can be determined via sensors. The data can then be used in an equation to determine a user's thermal comfort. The details of exemplary equations will be set forth below. The manner in which the equations are used will be discussed in conjunction with method 100.

With respect to FIG. 1, a method 100 is presented that illustrates the operation of one or more embodiments. Method 100 is merely exemplary and is not limited to the embodiments presented herein. Method 100 can be employed in many different embodiments or examples not specifically depicted or described herein. In some embodiments, the procedures, processes, and/or activities of method 100 can be performed in the order presented. In other embodiments, one or more of the procedures, processes, and/or activities of method 100 can be combined, skipped, or performed in a different order. In some embodiments, method 100 can be executed by a system 200. Method 100 details a training algorithm that can be used to determine thermal comfort of a guest. Interior environmental conditions are retrieved from a variety of sensors located in or near a room to be conditioned (block 102). These conditions can include temperature, humidity, air speed, mean radiant temperature (e.g., of objects in the room to be conditioned) and the like.

Mean radiant temperature is the temperature of an imaginary black enclosure which would result in the same heat loss by radiation from the person as the actual enclosure. Calculating mean radiant temperature would require the measuring the temperature of all surfaces in the room, as well as the angle factor between each surface and a person. Such a calculation would be very difficult and time consuming to perform. Therefore, approximations of mean radiant temperature can be used instead. For example, a Globe Temperature can be determined, with the mean radiant temperature determined from the globe temperature.

These can include integrated temperatures, such as operative temperature (t₀), equivalent temperature (t_(eq)), and effective temperature (ET*). In addition, a parameter called Operative Temperature also can be calculated. Operative Temperature at a given point is equal to the temperature an unheated mannequin dummy adjusts itself to. An Operative Temperature transducer can be used to determine Operative Temperature. Such a transducer is a light gray ellipsoid, 160 mm long with a diameter of 54 mm. The average surface temperature of that transducer is the operative temperature.

Outdoor environmental conditions are retrieved (block 104). Outdoor environmental conditions can be retrieved from sensors associated with the building. In some embodiments, outdoor environmental conditions can be retrieved from external sources, such as via the Internet.

Data regarding the room to be conditioned are retrieved (block 106). The data can include the dimensions of the room, objects within the room, purpose of the room, and the like. Objects within the room can include any objects that generate heat, such as electronics, refrigerators, computers, lighting, and the like. Purpose of the room includes information about which activities are typically performed in the room. For example, a room may typically be used for exercise. A room may typically be used for reading and research. A room may typically be used for sleeping.

A field of temperature, humidity, air speed, mean radiant temperature, and the like is created based on the data provided above (block 108). A field may mean that for a plurality of points in the room, the indoor environmental conditions are calculated. This can be accomplished in one of a variety of different manners. For example, the Kriging method can be used.

Kriging is a method of interpolation for which interpolated values are modeled by a Gaussian process that is governed by prior covariances. The basic idea of Kriging is to predict the value of a function at a given point by computing a weighted average of the known values of the function in the neighborhood of a point. Kriging is used for deriving a field for each indoor environmental variable for each room. By knowing the value of a quantity in some points in space (for example the temperature measured close to the entrance and opposite angles), we can determine the value of the magnitude at other points for which there are no measures, for example at the center of the room where there are not thermometers.

Estimates are generated regarding clothing insulation of the guest (block 110). Clothing of the guest can be estimated using a variety of different factors. For example, the outdoor environmental conditions are an indication of how much clothing a typical person could be wearing. However, outdoor environmental conditions may have a smaller effect depending on the location of the room and the typical use of the room. For example, a hotel lobby may have people still wearing outdoor clothing. However, people may take off their coat or jacket while in a restaurant or conference room in the same building. A clothing insulation value, discussed above, can be estimated during this block.

The thermal comfort of the user is calculated (block 112). The field of temperatures at a plurality of points (and other conditions relevant to thermal comfort, such as humidity and air velocity) generated in block 108 is used to calculate the thermal comfort at the same plurality of points. The thermal comfort can be estimated in one of a variety of different manners. For example, Fanger's Equation can be used to estimate a Predicted Mean Vote of the user. This can be calculated for each of the points for which the field was generated in block 108.

Fanger's equation provides for a calculation of a Predicted Mean Vote (PMV) based on a variety of different factors. The PMV can be a scale ranging from −3 (representing a value that is too cold), to positive 3 (representing a value that is too hot). A value of 0 would represent a thermally neutral sensation. In some embodiments, the scale may be a continuous scale, as opposed to being limited to only the integers between −3 and 3. Fanger's equation is presented in FIG. 2.

In equation 1, M represents the metabolic rate, measured in watts per square meter. W represents the effective mechanical power, in watts per square meter and can usually be set to zero. From a physical perspective, W measures the mechanical work done by an occupant. H represents dry heat losses. E_(c) represents the heat exchange by evaporation on the skin. C_(res) represents the heat exchange by convection in breathing. E_(res) represents the evaporative heat exchange in breathing.

Equations 2 through 5 illustrate how some of the variable in equation 1 are determined. In equation 2, H, the dry heat loss, is calculated using information regarding the clothing, such as clothing insulation, clothing surface area factor, and the air temperature. In equation 3, E_(c) is calculated using the metabolic rate and water vapor partial pressure (which is a component of relative humidity). In equation 4, the heat exchange is calculated using the metabolic rate and the temperature. In equation 5, the evaporative heat exchange is calculated using the metabolic rate and water vapor partial pressure (which is a component of relative humidity).

Thereafter, the HVAC systems can be set based on the thermal comfort data (block 114). For example, if the thermal comfort of the user indicates that the user is cold, a heater can be turned on. Similarly, if the thermal comfort equation indicates that the user is hot, air conditioning systems can be turned on.

Periodically, the user's opinions regarding the current thermal level can be gathered (block 116). The user's opinions can be gathered in a variety of different methods. For example, a software application (also known as an “app”) can be utilized by the user to provide their feedback as to their current comfort level.

If there deviations between the calculated thermal comfort (calculated in block 112) and the perceived thermal comfort (gathered in block 116), the HVAC can be re-adjusted (block 118). For a particular user, a thermal profile of the user can be saved (block 120). The profile of the user can include the user's characteristics regarding thermal comfort calculations. For example, the profile can indicate that the user typically feels colder (or warmer) than the calculated equations would show.

The profile can be retrieved whenever the user is in the room to be conditioned. In some embodiments, the room to be conditioned or the building in which the room is located, can retrieve the thermal profile and automatically use the thermal profile to make adjustments to the calculated thermal comfort. For example, when a user who is unusually sensitive to cold enters the building, the building can sense the user and automatically take that user into account when calculating thermal comfort. The building can be a “smart” building with multiple sensors that determines the presence and/or location of the user to make use of the user's thermal profile.

The above described method deals with a single user's thermal comfort. To determine how to condition for a group (for example, a room that contains multiple people), the PMV could be calculated for each person in the group. Thereafter, an average PMV can be used instead of the calculated thermal comfort (calculated in block 112).

In addition, a calculated PMV can be used to determine a predicted percentage of dissatisfied (PPD) for group settings. The PPD is shown as equation 6 in FIG. 2. In general, PPD shows how many people are dissatisfied with a certain PMV value. For example, it has been found that a PMV of plus or minus 1.5 results in 50 percent of people being dissatisfied. When calculating an average PMV, the PPD could be used as a constraint, to ensure that the percentage of people who are dissatisfied for a given set of conditions is as small as possible.

FIG. 3 depicts a high-level block diagram of a computer system 300, which can be used to implement one or more embodiments. More specifically, computer system 300 can be used to implement hardware components of systems capable of performing methods described herein. Although one exemplary computer system 300 is shown, computer system 300 includes a communication path 326, which connects computer system 300 to additional systems (not depicted) and can include one or more wide area networks (WANs) and/or local area networks (LANs) such as the Internet, intranet(s), and/or wireless communication network(s). Computer system 300 and additional system are in communication via communication path 326, e.g., to communicate data between them.

Computer system 300 includes one or more processors, such as processor 302. Processor 302 is connected to a communication infrastructure 304 (e.g., a communications bus, cross-over bar, or network). Computer system 300 can include a display interface 306 that forwards graphics, textual content, and other data from communication infrastructure 304 (or from a frame buffer not shown) for display on a display unit 308. Computer system 300 also includes a main memory 310, preferably random access memory (RAM), and can also include a secondary memory 312. Secondary memory 312 can include, for example, a hard disk drive 314 and/or a removable storage drive 316, representing, for example, a floppy disk drive, a magnetic tape drive, or an optical disc drive. Hard disk drive 314 can be in the form of a solid state drive (SSD), a traditional magnetic disk drive, or a hybrid of the two. There also can be more than one hard disk drive 314 contained within secondary memory 312. Removable storage drive 316 reads from and/or writes to a removable storage unit 318 in a manner well known to those having ordinary skill in the art. Removable storage unit 318 represents, for example, a floppy disk, a compact disc, a magnetic tape, or an optical disc, etc. which is read by and written to by removable storage drive 316. As will be appreciated, removable storage unit 318 includes a computer-readable medium having stored therein computer software and/or data.

In alternative embodiments, secondary memory 312 can include other similar means for allowing computer programs or other instructions to be loaded into the computer system. Such means can include, for example, a removable storage unit 320 and an interface 322. Examples of such means can include a program package and package interface (such as that found in video game devices), a removable memory chip (such as an EPROM, secure digital card (SD card), compact flash card (CF card), universal serial bus (USB) memory, or PROM) and associated socket, and other removable storage units 320 and interfaces 322 which allow software and data to be transferred from the removable storage unit 320 to computer system 300.

Computer system 300 can also include a communications interface 324. Communications interface 324 allows software and data to be transferred between the computer system and external devices. Examples of communications interface 324 can include a modem, a network interface (such as an Ethernet card), a communications port, or a PC card slot and card, a universal serial bus port (USB), and the like. Software and data transferred via communications interface 324 are in the form of signals that can be, for example, electronic, electromagnetic, optical, or other signals capable of being received by communications interface 324. These signals are provided to communications interface 324 via communication path (i.e., channel) 326. Communication path 326 carries signals and can be implemented using wire or cable, fiber optics, a phone line, a cellular phone link, an RF link, and/or other communications channels.

In the present description, the terms “computer program medium,” “computer usable medium,” and “computer-readable medium” are used to refer to media such as main memory 310 and secondary memory 312, removable storage drive 316, and a hard disk installed in hard disk drive 314. Computer programs (also called computer control logic) are stored in main memory 310 and/or secondary memory 312. Computer programs also can be received via communications interface 324. Such computer programs, when run, enable the computer system to perform the features discussed herein. In particular, the computer programs, when run, enable processor 302 to perform the features of the computer system. Accordingly, such computer programs represent controllers of the computer system. Thus it can be seen from the forgoing detailed description that one or more embodiments provide technical benefits and advantages.

Referring now to FIG. 4, a computer program product 400 in accordance with an embodiment that includes a computer-readable storage medium 402 and program instructions 404 is generally shown.

Embodiments can be a system, a method, and/or a computer program product. The computer program product can include a computer-readable storage medium (or media) having computer-readable program instructions thereon for causing a processor to carry out aspects of embodiments of the present invention.

The computer-readable storage medium can be a tangible device that can retain and store instructions for use by an instruction execution device. The computer-readable storage medium can be, for example, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. A non-exhaustive list of more specific examples of the computer-readable storage medium includes the following: a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanically encoded device such as punch-cards or raised structures in a groove having instructions recorded thereon, and any suitable combination of the foregoing. A computer-readable storage medium, as used herein, is not to be construed as being transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission media (e.g., light pulses passing through a fiber-optic cable), or electrical signals transmitted through a wire.

Computer-readable program instructions described herein can be downloaded to respective computing/processing devices from a computer-readable storage medium or to an external computer or external storage device via a network, for example, the Internet, a local area network, a wide area network and/or a wireless network. The network can comprise copper transmission cables, optical transmission fibers, wireless transmission, routers, firewalls, switches, gateway computers, and/or edge servers. A network adapter card or network interface in each computing/processing device receives computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium within the respective computing/processing device.

Computer-readable program instructions for carrying out embodiments can include assembler instructions, instruction-set-architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state-setting data, or either source code or object code written in any combination of one or more programming languages, including an object-oriented programming language such as Smalltalk, C++ or the like, and conventional procedural programming languages, such as the “C” programming language or similar programming languages. The computer-readable program instructions can execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computer (for example, through the Internet using an Internet Service Provider). In some embodiments, electronic circuitry including, for example, programmable logic circuitry, field-programmable gate arrays (FPGA), or programmable logic arrays (PLA) can execute the computer-readable program instructions by utilizing state information of the computer-readable program instructions to personalize the electronic circuitry, in order to perform embodiments of the present invention.

Embodiments may be implemented using one or more technologies. In some embodiments, an apparatus or system may include one or more processors and memory storing instructions that, when executed by the one or more processors, cause the apparatus or system to perform one or more methodological acts as described herein. Various mechanical components known to those of skill in the art may be used in some embodiments.

Embodiments may be implemented as one or more apparatuses, systems, and/or methods. In some embodiments, instructions may be stored on one or more computer program products or computer-readable media, such as a transitory and/or non-transitory computer-readable medium. The instructions, when executed, may cause an entity (e.g., a processor, apparatus or system) to perform one or more methodological acts as described herein.

While the present disclosure has been described with reference to an exemplary embodiment or embodiments, it will be understood by those skilled in the art that various changes may be made and equivalents may be substituted for elements thereof without departing from the scope of the present disclosure. In addition, many modifications may be made to adapt a particular situation or material to the teachings of the present disclosure without departing from the essential scope thereof. Therefore, it is intended that the present disclosure not be limited to the particular embodiment disclosed as the best mode contemplated for carrying out this present disclosure, but that the present disclosure will include all embodiments falling within the scope of the claims. 

1. A computer-implemented method for conditioning an interior area comprising: retrieving environmental conditions regarding the interior area, wherein the environmental conditions include temperature, humidity, and air speed; retrieving outdoor environmental conditions; generating a field of environmental conditions at a plurality of points within the interior area; calculating a thermal comfort of the user to determine a predicted mean vote; and operating a heating, ventilation, and air conditioning system based on the calculated thermal comfort.
 2. The computer-implemented method of claim 1, further comprising: retrieving usage information regarding the interior area.
 3. The computer-implemented method of claim 2, further comprising estimating clothing insulation of a user based on the outdoor environmental conditions and the usage information.
 4. The computer-implemented method of claim 1, further comprising: receiving feedback from the user regarding the user's comfort level; and operating the heating, ventilation, and air conditioning system based on the feedback.
 5. The computer-implemented method of claim 4, further comprising: storing the feedback in a thermal profile associated with the user.
 6. The computer-implemented method of claim 5, wherein: calculating the thermal comfort of the user comprises using the thermal profile to calculate the thermal comfort.
 7. The computer-implemented method of claim 1, wherein: calculating the thermal comfort of the user comprises using a Fanger equation to calculate the predicted mean vote.
 8. The computer-implemented method of claim 7, wherein: the predicted mean vote is on a continuous scale ranging from −3 to 3, wherein a value of −3 indicates a cold thermal condition and a value of 3 indicates a warm thermal condition.
 9. The computer-implemented method of claim 1, further comprising: calculating the thermal comfort for each user of a plurality of users in the interior area; and calculating an average thermal comfort for the plurality of users; wherein: operating a heating, ventilation, and air conditioning system is based on the average thermal comfort of the plurality of users.
 10. The computer-implemented method of claim 9, further comprising: calculating a predicted percentage of dissatisfied users based on the thermal comfort of each of the plurality of users; wherein: operating a heating, ventilation, and air conditioning system further comprises ensuring that the predicted percentage of dissatisfied users is below a predetermined threshold.
 11. A computer system for facilitating anonymous and automated communication comprising: a processor; a memory; computer program instructions configured to cause the processor to perform the following method: retrieving environmental conditions regarding the interior area, wherein the environmental conditions include temperature, humidity, and air speed; retrieving outdoor environmental conditions; generating a field of environmental conditions at a plurality of points within the interior area; calculating a thermal comfort of the user to determine a predicted mean vote; and operating a heating, ventilation, and air conditioning system based on the calculated thermal comfort.
 12. The computer system of claim 11, wherein the method further comprises: retrieving usage information regarding the interior area.
 13. The computer system of claim 12, wherein: estimating clothing insulation of a user based on the outdoor environmental conditions and the usage information.
 14. The computer system of claim 11, wherein the method further comprises: receiving feedback from the user regarding the user's comfort level; and operating the heating, ventilation, and air conditioning system based on the feedback.
 15. The computer system of claim 14, wherein the method further comprises: storing the feedback in a thermal profile associated with the user.
 16. The computer system of claim 15, wherein: calculating the thermal comfort of the user comprises using the thermal profile to calculate the thermal comfort.
 17. The computer system of claim 11, wherein: calculating the thermal comfort of the user comprises using a Fanger equation to calculate the predicted mean vote.
 18. The computer system of claim 17, wherein: the predicted mean vote is on a continuous scale ranging from −3 to 3, wherein a value of −3 indicates a cold thermal condition and a value of 3 indicates a warm thermal condition.
 19. The computer system of claim 11, wherein the method further comprises: calculating the thermal comfort for each user of a plurality of users in the interior area; and calculating an average thermal comfort for the plurality of users; wherein: operating a heating, ventilation, and air conditioning system is based on the average thermal comfort of the plurality of users.
 20. The computer system of claim 19, wherein the method further comprises: calculating a predicted percentage of dissatisfied users based on the thermal comfort of each of the plurality of users; wherein operating a heating, ventilation, and air conditioning system further comprises ensuring that the predicted percentage of dissatisfied users is below a predetermined threshold. 